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Record W2140327171 · doi:10.1002/art.38483

A67: Factors That Contribute to Classification of Children as Having Undifferentiated Juvenile Idiopathic Arthritis

2014· article· en· W2140327171 on OpenAlexaffabout
Mercedes Chan, Ross E. Petty, Kiem Oen, Ciarán M. Duffy, Lori B. Tucker, Rae S. M. Yeung, Jaime Guzmán

Bibliographic record

VenueArthritis & Rheumatology · 2014
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of OttawaUniversity of ManitobaHospital for Sick ChildrenUniversity of British ColumbiaChildren's Hospital of WinnipegUniversity of TorontoBC Children's Hospital
Fundersnot available
KeywordsJuvenileArthritisPsychologyMedicineDevelopmental psychologyImmunologyBiologyGenetics

Abstract

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Background/Purpose: According to the ILAR criteria, undifferentiated juvenile idiopathic arthritis (U‐JIA) includes children who fail to meet criteria for 1 of the other 6 categories or who meet criteria in more than 1 category. Classification requires category‐specific application of 5 exclusion criteria: 1. Psoriasis in the patient or a 1st degree relative; 2. Arthritis beginning after the 6th birthday in an HLA‐B27 + male; 3. HLAB27 associated disease in a 1st degree relative; 4. Rheumatoid factor positivity (RF+) on 2 occasions; and 5. The presence of systemic JIA (SoJIA). A pilot single‐centre study (n=21) revealed that psoriasis in a 1st degree relative was the most common reason for classifying patients as U‐JIA; disregarding this criterion would allow re‐classification of most U‐JIA patients and had no impact on the classification of JPsA patients (Chan et al., 2011). We aimed to determine the most frequent reasons for classifying children as U‐JIA from a large multicenter prospective cohort of children with JIA (n=1104). Methods: Two investigators reviewed data on patients diagnosed with UJIA extracted from the Research in Arthritis in Canadian Children emphasizing Outcomes (ReACCh‐Out) database. They identified by consensus the reasons for classifying patients as U‐JIA and the JIA category they would fall in if the following two changes were made: disregarding psoriasis in a 1st degree relative, considering patients as RF negative when only a single positive RF test was recorded. Results: 84 patients (51 female), were classified as U‐JIA for the reasons shown in the . Exclusion criteria 1st degree relative with psoriasis (n=57) B27 male>6 years + arthritis (n=4) RF+ on 2 occasions (n=1) RF+ on 1 occasion only (n=17) 1st degree relative with B27 related disease (n=4) SoJIA (n=0) Fulfills criteria for 2 categories (n=2) Revised category if exclusion criteria disregarded Oligo 25 9 2 Poly RF− 13 2 Poly RF+ 5 (1 RF+x2, 4 RF+x1) ERA 12 5 Systemic 2 1 JPsA 4 1 U‐JIA 1 1 2 (JPsA + ERA) If the criterion of having a 1st degree relative with psoriasis was disregarded, 25 patients would be classified as oligo JIA, 13 poly RF−, 5 poly RF+, 12 ERA and 2 SoJIA. If a single positive RF test was considered to be insufficient to meet the ILAR criterion of RF positivity, 9 patients would be re‐classified as oligo JIA, 5 ERA, 1 SoJIA, 1 JPsA and 1 would remain U‐JIA. Conclusion: Psoriasis in a 1st degree relative is the most common factor contributing to the classification of a child as having U‐JIA and removing it from the existing criteria should be considered. The presence of a single positive test for RF was the second most common reason resulting in a classification of U‐JIA. Definitive RF testing (two tests) should be maintained to satisfy the criterion of “RF positivity”.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.270
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2014
Admission routes2
Has abstractyes

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